I build predictive models and BI dashboards that drive revenue, minimize risk, and enable smarter business decisions.

Data Science | Product Analytics | Risk Modeling
I am a Data Professional who operates at the intersection of Data Science and Product Analytics. I specialize in turning messy, unstructured data into clear answers for business stakeholders.
My experience is hands-on: I’ve developed credit-risk models, analyzed user behavior for product teams, and built automated reporting pipelines. I combine the technical depth of a Data Scientist with the business clarity of an Analyst.
Core Stack: Python (Pandas/Scikit-learn), SQL, Tableau, Power BI, AWS, and Machine Learning.
Professional Impact
Modeled multinational corporate performance trends using Python (Pandas, Seaborn) to uncover growth patterns. Cleaned and structured complex financial datasets using SQL to track revenue and market share metrics.
Improved reporting reliability by 20% through SQL and Python cleaning protocols. Managed scheduling algorithms for faculty to maximize operational efficiency.
Designed BI dashboards in Power BI to visualize macroeconomic trends, translating raw data into clear insights for stakeholders. Replaced manual data tasks with automated workflows.
Designed a data system that improved operational efficiency by 25%. Centralized unstructured data into a SQL repository for real-time tracking and trained 20+ staff members on new data tools.
A collection of practical, data-centered projects demonstrating my skills in analytics, modeling, and business intelligence.
Technologies and tools I work with
Academic Background
Relevant Coursework: Predictive Modeling, Advanced Machine Learning, Database Management (SQL), Cloud Computing (AWS), Financial Risk Analytics.
Focus: Internet Systems, Data Architecture, Information Technology Strategy.
Focus: Computer Science Fundamentals, Algorithms, Software Engineering.
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